Public Health Policy and Administration (PHPA) faculty include: D. Phuong (Phoenix) Do, Mustafa Hussein, Linnea Laestadius, and Yang Wang. Current PHPA research explores the role of policy in influencing population health, as well as the drivers for policy development. This multidisciplinary program includes research on food systems and environmental policy, immigration and detention policy, immigration and detention policy, neighborhood context, residential racial and economic segregation, health services and healthcare among immigrants and vulnerable populations, violence, and the social determinants of health inequities. Learn more about featured research projects by PHPA faculty:
Electronic health (e-health) services have become critical to health care provision as information technologies influence and shape how physicians practice and communicate with patients. Those services can reduce indirect costs associated with seeking care meanwhile improve access and clinical outcomes. Little research has examined differences in utilizing e-health services across immigration status nationwide. In this study, we categorize into three groups including US native, naturalized citizen, and noncitizen, based on their citizenship and place of birth. Our outcome variable of interest is if they had any e-health services during the past 12 months. Univariate analyses characterizes the trend of using e-health services by immigrant status over the study period. Multivariate logistic regression models examines the association between immigration status and the likelihood of using e-health services, controlling for demographic characteristics, socioeconomic status, and health status. We also examine the impact of acculturation on the use of e-health services among immigrants.
Many cities in the US enacted living wage policies in the 1990s, thanks to unrelenting community-organizing efforts and labor market activism across urban communities. These policies aimed to lift low-wage workers out of poverty, by often indexing the minimum wage floors in those jurisdictions to the federal poverty level. The economic effects of these policies appear to be sizable, despite limited coverage in the target population. Little is known, however, about the impact of these policies on health or health inequalities. This work uses quasi-experimental methods to derive estimates of the effects of living wage policies on inequalities in mental and physical health, as well as access to healthcare, by race/ethnicity, gender, and socioeconomic position.
Estimating the causal impact of neighborhood effects from observational data has proven to be a challenge. Omission of relevant factors may lead to overestimating the effects of neighborhoods on health while inclusion of time-varying confounders that may also be mediators (e.g., income, labor force status) may lead to underestimation. Because policy inferences and anticipated impacts of interventions rely on estimates of causal versus associational connections, addressing these sources of bias are important to make appropriate policy recommendations. Using longitudinal data from the 1999 to 2013 years of the Panel Study of Income Dynamics, this study investigates the link between neighborhood poverty and body weight. We address the issue of possible downward bias due to adjusting for mediating factors by employing a marginal structural modeling strategy, which appropriately adjusts for simultaneous mediating and confounding factors. We then compare conventional naïve estimates to those recovered from marginal structural modeling. To address the issue of possible upward bias due to omitted variables, we conduct a sensitivity analysis to assess the robustness of results against unobserved confounding.
Large-scale industrial farm animal production (IFAP) operations have been associated with a number of health concerns for individuals residing near facilities. This study sought to examine the ways in which state and local agencies respond to and prevent community-driven health concerns associated with IFAP facilities. An initial manuscript focused on state and county health department responses was published in PLOS ONE in 2013. A follow up manuscript examining state departments of agriculture and facility permitting agencies is currently under review.
Though neighborhood conditions, such as poverty and disorder, are thought to be the primary means through which segregation affects health, we know very little about how segregation and neighborhoods interact together to influence the health. Are the effects of metropolitan segregation conditioned on neighborhood factors or are the effects uniform across all neighborhood types? Do the effects of neighborhood-level (local) segregation on health differ from the effects of metropolitan- level (metro) segregation? Using data from the National Health Interview Survey, this study comprehensively examines the interconnections between metropolitan segregation, neighborhood context, and individual health. We utilize spatial measures of metro and local segregation, account for neighborhood conditions, and apply three-level hierarchal models to asses how contextual factors at different levels interact to affect the health of blacks, Hispanics, and whites in the U.S. This fundamental determinants perspective underscores the potentially immense impact of housing policies, urban design, and the spatial allocation of resources and risk exposures to combat the root cause of racial/ethnic health disparities in the U.S.
Racial/ethnic differences in obesity, an epidemic in the U.S., are only partially accounted for by individual-level socioeconomic status, suggesting that examination of the causes and correlates of overweight and obesity ought to include other factors patterned by race and ethnicity, including various features of the environments in which groups live. Using the longitudinal data from the Multi-ethnic Study of Atherosclerosis (MESA), this study investigates the association between local spatial measures of segregation and BMI and whether these associations differ between blacks, Hispanics, and whites. We also investigate whether specific physical and social features of neighborhoods (e.g., social cohesion, safety, food access) explain any associations found. Three- level hierarchal models with repeated measures nested within persons nested within neighborhoods are applied across multiple MESA sites, providing a detailed and comparative analysis of the relationship between local segregation and BMI across multiple cities in the U.S.